Defining Quality with Clarity


If you’re reading this, I’m assuming you earn your living in some sort of Quality Organization, but do you Speak Quality? And if you do, can you speak it fluently, or are you topped out at the conversational level?

The reality is, if you’re like many people in Quality Organizations, you may not know. But if you find yourself explaining anecdotally, or relying on your organization’s acronyms to make your point, you may also find that you struggle to apply Quality concepts.

If so, I wrote this month’s blog for you.
This installment will focus on some critical fundamentals:

  • The relationship between control and Quality
  • The nature of Quality Control, within the larger construct of Quality Assurance
  • The components of Quality Assurance within a larger Quality Management System


Begin at The Beginning: Quality is a Function of Control


Before we evaluate the relationship of Quality Assurance and Quality Control, let’s first remind ourselves, that the cGMPs fundamental principle is that Quality is a function of Control.

All of our Quality models are developed with this fundamental in mind.

Understand Quality

But what precisely is Quality? The long answer may depend on:

  • Whether or not you are contributing to production of a product, or you are a consumer of a product
  • The type of industry you work for (regulated or non-regulated)
  • Your function within industry

In an earlier installment of the blog, we reviewed the results of the 2012 ASQ World Quality Month poll that queried members about their definitions. Not surprisingly, this is what they found:

  • Consumers defined quality as having their functional and aesthetic expectations met for a low cost
  • Retailers defined quality as having satisfied their consumers
  • Engineers defined quality as increased efficiency and reduction of defects
  • Manufactures defined quality as having produced defect-free product, on time, and for as high a profit margin as possible
  • Sales people and marketers defined quality almost entirely in terms of customer perception


Is the granular detail clarifying the concept for you, or is it adding to the confusion? For this installment’s purposes, we’ll combine all of those definitions into a single sentence:

Plan and Confirm Quality: Quality Assurance and Quality Control

Now that we have the definition of Quality distilled to a manageable size that seems to suit everyone, let’s focus on two labels that are familiar to everyone functioning within a manufacturing environment, but that continue to be confused with each other.
Quality Assurance (QA) and Quality Control (QC) are labels that sound alike, and have a wildly important relationship to each other, but one of the first steps in learning to Speak Quality fluently is to recognize that they are not identical, nor interchangeable.

There are many published definitions of Quality Assurance, and of Quality Control.  The table below reviews some of the most commonly referred to definitions:


Fundamentally, we realize that no matter what level of control we believe that we have achieved post development and validation, we will still need to confirm that we have maintained control throughout processing and that we collect data on a lot-to-lot, or device-to-device basis that allows us to recognize trends.
QC is the tool that QA uses to execute these data collection steps.
In addition to requiring manufacturing procedures for operations, QA also prescribes procedures and sampling plans for QC that are designed to:
  1. Monitor the routine manufacturing processes while they are being executed to confirm adherence to Critical Processing Parameters (CPPs).
  2. Measure the Critical Quality Attributes (CQAs) of the product to ensure that execution of operations processes resulted in product that met CQAs (for immediate use in lot release).
  3. Report the actual CPPs achieved in relation to the CQAs produced for each lot or device, both for product release and trending purposes (routine trending data feeds Continual Improvement efforts).
It is worth noting that the acceptance criteria applied to QC activities are standards, specifications, and attributes that were previously defined by QA.
The reactive steps that should be taken in response to QC test results are also proactively defined by QA, and will generally be one of the following:
  1. Release of product if all CPPs have been adhered to and all CQAs have been met
  2. Documentation and investigation of processing deviations and quarantine of product, if CPPs have not been met.
  3. Documentation and investigation of product failure and rejection of product, if CQAs have not been met.
In cases where the absent indicator is adherence to CPPs, further investigation by QA may indicate that even though defined CPPs were not met, the Quality of the end product itself (CQAs) may still support release of that lot.  In those cases, this information may also lead to an improvement to the process, e.g., redefinition of acceptable CPPs.
As the nature of QC comes during and after production, it should now be easy to see that QC cannot ensure quality; its role is limited to the identification of instances that lack the indicators of Quality.
It is worth noting, that these indicators (CPPs and CQAs) were also defined earlier in the product life cycle by QA.

Managing and Maintaining: Quality Management and Quality Systems

As the quality movement matured and improved, it developed into Quality Management, shifting the emphasis to include systems thinkingand management systems.  The scope of Quality Management includes not only production-based quality planning and management review, Quality Assurance, Quality Control, and various other control programs (see diagram below), but also seeks to build the body of knowledge developed during routine production, to perpetually seek opportunities for improvement.

This maturation of the Quality Model (building systems, instead of just building product) is a realization that an understanding of how components affect each other cannot be developed by knowing only the components. We now recognize that there are some issues and assets that effect all stages of manufacturing including talent, knowledge, and tools, as illustrated in the following diagram.

The diagram above illustrates this systems-based management approach by:
  • Placing the control systems in an outer concentric ring, as each occupies a space in time throughout the product lifecycle.  Each control system is designed to mitigate an identified risk and, sequentially, increase the level of control by reducing the potential variance that we can expect when we routinely manufacture.
  • Encompassing each of the control systems within a dotted line component; those components are regularly executed assessment tools, put in place to evaluate compliance with, and the effectiveness of, those control processes.
The control processes, and the corresponding assessment processes, will produce output that will be monitored continuously by cross functional management, in effect, giving them production-based data and information about the systems that generated that data.
We have come to understand that the most important measure of assuring Quality is the quality of the decision-making process itself, and the best decisions are always data driven.
Sound and robust systems seek to:
  • Develop our understanding of the impact of our processes and the effects of our actions
  • Address and utilize universal issues and assets consistently
  • Identify trends and highlight relationships between upstream activities and downstream  results
  • Provide the most current, relevant, and objective information possible, allowing decision makers to make data-driven decisions geared toward the general goal of improvement
  • Recognize that the supply chain is made up by multiple and equally critical perspectives, and facilitate consensus between them by introducing each to the system at the appropriate point in time
The systems approach has a distinct perspective – an eye on the interactivity of controls and continuous improvement.  And as such, this builds improvement tools into system integration points.  Tools such as:
  • Lean tools to reduce waste
  • Six Sigma methodology to reduce variation
  • Operational Excellence ideology to set goals
  • Trending tools that promote managing with metrics


QA focuses on defining controls and processes and driving toward their continuous improvement.Its goal is to reduce variance in processes through process controls in order to optimize the probability of output quality (final or interim product).  Along the way, it also deploys processes that assess the controls; gathering information in order to make data driven choices that lead to improving the best practices for the company, cost reduction, and reduction of time to market.
QC is one of the tools defined and deployed by QA.  It provides in-process checks and post production product measurements; optimizing the probability of identifying any absence of Quality indicators.
QM is the mature model of the cross-functional, systems based, programmatic manner of integrating QA efforts to every phase of the product lifecycle.This cross-functional manner of thinking and communicating aims to assure Quality by assessing and mitigating risk, reducing variance, eliminating waste by promoting lean manufacturing, and using the output of those systems to develop the knowledge base and continually improve.
A simple cross functional approach to Quality Management is the PDCA (Plan Do Check Act) Cycle:
  1. Plan:
  • Define the mission, vision, and goals (standards and specifications) to be achieved by an activity or a process.
  • Identify the procedures, methods, and tools needed to achieve the goals (training, audits, supplier control, equipment and facility/utility control, validation, change management, in-process confirmation, in-process monitoring, final release testing, failure investigation, CAPA, and continuous improvement systems).
  • Define the measures to be used to check the results of the process (procedures, methods, and acceptance criteria).
     2.  Do: Execute the plan, train users to methods, deploy products, and use tools to perform scheduled  tasks.
     3.  Check: Evaluate whether or not the goals have been achieved by using measures, metrics, and facts (i.e., reviewing and approving the output of all the tools deployed).
     4.  Act: When gaps are defined, identify the origin of the problem and define an approach to correct or close the gap (Return to the Plan phase by leading investigation, CAPA, and CI efforts).
We hope that this installment has clarified these concepts for our readers, so that they view their role in Quality Organization with clarity.

As always, we at Coda seek to provide Perspective with Purpose, in order to define Quality with Clarity!

© Coda Corp USA 2015.  All rights reserved.
Gina Guido-Redden
Post a comment or leave a trackback: Trackback URL.

Post a Comment

Your email is never published nor shared. Required fields are marked *


You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>